The impact of individual scientists is commonly quantified using citation-based measures. The most common such measure is the h-index. A scientist's h-index affects hiring, promotion, and funding decisions, and thus shapes the progress of science. Here we report a large-scale study of scientometric measures, analyzing millions of articles and hundreds of millions of citations across four scientific fields and two data platforms. We find that the correlation of the h-index with awards that indicate recognition by the scientific community has substantially declined. These trends are associated with changing authorship patterns. We show that these declines can be mitigated by fractional allocation of citations among authors, which has been discussed in the literature but not implemented at scale. We find that a fractional analogue of the h-index outperforms other measures as a correlate and predictor of scientific awards. Our results suggest that the use of the h-index in ranking scientists should be reconsidered, and that fractional allocation measures such as h-frac provide more robust alternatives. An interactive visualization of our work can be found at https://h-frac.org
翻译:科学家个人的影响通常通过以引证为基础的措施加以量化。最常见的此类措施是h-index。科学家的h-index影响聘用、晋升和供资决定,从而影响科学进步。我们在这里报告对科学计量的大规模研究,分析了四个科学领域和两个数据平台的数百万篇文章和数以亿计的引文。我们发现,h-index与表明科学界承认的奖项的相关性已经大大下降。这些趋势与作者模式的变化有关。我们表明,这些下降可以通过作者对引文的分数分配来缓解,这些引文已在文献中讨论过,但没有在规模上执行。我们发现,该h-index的分数模拟比其他措施更能成为科学奖项的关联性和预测。我们的结果表明,应当重新考虑在排名科学家中使用h-frac等指数的情况,以及像h-frac这样的分数分配措施提供了更可靠的替代方法。我们工作的交互视觉化可见https://h-frac.org。